Using cubic splines to mitigate systematic errors in GPS relative positioning

Systematic errors can have a significant effect on GPS observable. In medium and long baselines the major systematic error source are the ionosphere and troposphere refraction and the GPS satellites orbit errors. But, in short baselines, the multipath is more relevant. These errors degrade the accuracy of the positioning accomplished by GPS. So, this is a critical problem for high precision GPS positioning applications. Recently, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique. It uses a natural cubic spline to model the errors as a function which varies smoothly in time. The systematic errors functions, ambiguities and station coordinates, are estimated simultaneously. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method.

Modifying the stochastic model to mitigate GPS systematic errors in relative positioning

The GPS observables are subject to several errors. Among them, the systematic ones have great impact, because they degrade the accuracy of the accomplished positioning. These errors are those related, mainly, to GPS satellites orbits, multipath and atmospheric effects. Lately, a method has been suggested to mitigate these errors: the semiparametric model and the penalised least squares technique (PLS). In this method, the errors are modeled as functions varying smoothly in time. It is like to change the stochastic model, in which the errors functions are incorporated, the results obtained are similar to those in which the functional model is changed. As a result, the ambiguities and the station coordinates are estimated with better reliability and accuracy than the conventional least square method (CLS). In general, the solution requires a shorter data interval, minimizing costs. The method performance was analyzed in two experiments, using data from single frequency receivers. The first one was accomplished with a short baseline, where the main error was the multipath. In the second experiment, a baseline of 102 km was used. In this case, the predominant errors were due to the ionosphere and troposphere refraction. In the first experiment, using 5 minutes of data collection, the largest coordinates discrepancies in relation to the ground truth reached 1.6 cm and 3.3 cm in h coordinate for PLS and the CLS, respectively, in the second one, also using 5 minutes of data, the discrepancies were 27 cm in h for the PLS and 175 cm in h for the CLS. In these tests, it was also possible to verify a considerable improvement in the ambiguities resolution using the PLS in relation to the CLS, with a reduced data collection time interval. © Springer-Verlag Berlin Heidelberg 2007.

An effective wavelet method to detect and mitigate low-frequency multipath effects

To ensure high accuracy results from GPS relative positioning, the multipath effects have to be mitigated. Although the careful selection of antenna site and the use of especial antennas and receivers can minimize multipath, it cannot always be eliminated and frequently the residual multipath disturbance remains as the major error in GPS results. The high-frequency multipath from large delays can be attenuated by double difference (DD) denoising methods. But the low-frequency multipath from short delays is very difficult to be reduced or modeled. In this paper, it is proposed a method based on wavelet regression (WR), which can effectively detect and reduce the low-frequency multipath. The wavelet technique is firstly applied to decompose the DD residuals into the low-frequency bias and high-frequency noise components. The extracted bias components by WR are then directly applied to the DD observations to correct them from the trend. The remaining terms, largely characterized by the high-frequency measurement noise, are expected to give the best linear unbiased solutions from a least-squares (LS) adjustment. An experiment was carried out using objects placed close to the receiver antenna to cause, mainly, low-frequency multipath. The data were collected for two days to verify the multipath repeatability. The ground truth coordinates were computed with data collected in the absence of the reflector objects. The coordinates and ambiguity solution were compared with and without the multipath mitigation using WR. After mitigating the multipath, ambiguity resolution became more reliable and the coordinates were more accurate.

Tropical tanniniferous legumes used as an option to mitigate sheep enteric methane emission

This study presents the first results from Brazil using SF6 tracer technique adapted from cattle to evaluate the capability of condensed tannin (CT) present in three tropical legume forages, Leucaena leucocephala (LEU), Styzolobium aterrimum (STA), and Mimosa caesalpiniaefolia Benth (MIM) to reduce enteric CH4 production in Santa Ins sheep. Twelve male lambs [27.88 +/- 2.85 kg body weight (BW)] were allocated in individual metabolic cages for 20-day adaptation followed by 6 days for measuring dry matter intake (DMI) and CH4 emission. All lambs received water, mineral supplement, and Cynodon dactylon v. coast-cross hay ad libitum. The treatments consisted of soybean meal (710 g/kg) and ground corn (290 g/kg) [control (CON)]; soybean meal (150 g/kg), ground corn (30 g/kg), and Leucaena hay (820 g/kg) (LEU); soybean meal (160 g/kg), ground corn (150 g/kg), and Mucuna hay (690 g/kg) (STA); and soybean meal (280 g/kg), ground corn (190 g/kg), and Mimosa hay (530 g/kg) (MIM); all calculated to provide 40 g/kg CT (except for CON). DMI (in grams of DMI per kilogram BW per day) was lower for LEU (22.0) than CON (29.3), STA (31.2), and MIM (31.6). The LEU group showed emission of 7.8 g CH4/day, significantly lower than CON (10.5 g CH4/day), STA (10.4 g CH4/day), and MIM (11.3 g CH4/day). However, when the CH4 emission per DMI was considered, there were no significant differences among treatments (0.37, 0.36, 0.33, and 0.35 g CH4/g DMI/kg BW/day, respectively, for CON, LEU, STA, and MIM). The sheep receiving STA had shown a tendency (p = 0.15) to reduce methane emission when compared to the CON group. Therefore, it is suggested that tropical tanniniferous legumes may have potential to reduce CH4 emission in sheep, but more research is warranted to confirm these results.

An approach to mitigate denial of service attacks in ieee 802.11 networks

Wireless networks are widely deployed and have many uses, for example in critical embedded systems. The applications of this kind of network meets the common needs of most embedded systems and addressing the particularities of each scenario, such as limitations of computing resources and energy supply. Problems such as denial of service attacks are common place and cause great inconvenience. Thus, this study presents simulations of denial of service attacks on 802.11 wireless networks using the network simulator OMNeT++. Furthermore, we present an approach to mitigate such attack, obtaining significant results for improving wireless networks.

Contributions to effective protocol design to mitigate continuous multimedia services short disriptions in WiFi networks

Eliminadas las páginas en blanco

OpenMP task scheduling strategies to mitigate hardware variability in tightly-coupled shared memory clusters

In questa tesi sono stati apportati due importanti contributi nel campo degli acceleratori embedded many-core. Abbiamo implementato un runtime OpenMP ottimizzato per la gestione del tasking model per sistemi a processori strettamente accoppiati in cluster e poi interconnessi attraverso una network on chip. Ci siamo focalizzati sulla loro scalabilità e sul supporto di task di granularità fine, come è tipico nelle applicazioni embedded. Il secondo contributo di questa tesi è stata proporre una estensione del runtime di OpenMP che cerca di prevedere la manifestazione di errori dati da fenomeni di variability tramite una schedulazione efficiente del carico di lavoro.

Utilizing Gaussian-Schell model beams to mitigate atmospheric turbulence in free space optical communications / by Kyle R. Drexler.

Turbulence affects traditional free space optical communication by causing speckle to appear in the received beam profile. This occurs due to changes in the refractive index of the atmosphere that are caused by fluctuations in temperature and pressure, resulting in an inhomogeneous medium. The Gaussian-Schell model of partial coherence has been suggested as a means of mitigating these atmospheric inhomogeneities on the transmission side. This dissertation analyzed the Gaussian-Schell model of partial coherence by verifying the Gaussian-Schell model in the far-field, investigated the number of independent phase control screens necessary to approach the ideal Gaussian-Schell model, and showed experimentally that the Gaussian-Schell model of partial coherence is achievable in the far-field using a liquid crystal spatial light modulator. A method for optimizing the statistical properties of the Gaussian-Schell model was developed to maximize the coherence of the field while ensuring that it does not exhibit the same statistics as a fully coherent source. Finally a technique to estimate the minimum spatial resolution necessary in a spatial light modulator was developed to effectively propagate the Gaussian-Schell model through a range of atmospheric turbulence strengths. This work showed that regardless of turbulence strength or receiver aperture, transmitting the Gaussian-Schell model of partial coherence instead of a fully coherent source will yield a reduction in the intensity fluctuations of the received field. By measuring the variance of the intensity fluctuations and the received mean, it is shown through the scintillation index that using the Gaussian-Schell model of partial coherence is a simple and straight forward method to mitigate atmospheric turbulence instead of traditional adaptive optics in free space optical communications.

Appraising and selecting conservation measures to mitigate desertification and land degradation based on stakeholder participation and global best practices

Most desertification research focuses on degradation assessments without putting sufficient emphasis on prevention and mitigation strategies, although the concept of Sustainable Land Management (SLM) is increasingly being acknowledged. A variety of already applied conservation measures exist at the local level, but they are not adequately recognised, evaluated and shared, either by land users, technicians, researchers, or policy makers. Likewise, collaboration between research and implementation is often insufficient. The aim of this paper is to present a new methodology for a participatory process of appraising and selecting desertification mitigation strategies, and to present first experiences from its application in the EU-funded DESIRE project. The methodology combines a collective learning and decision approach with the use of evaluated global best practices. In three parts, it moves through a concise process, starting with identifying land degradation and locally applied solutions in a stakeholder workshop, leading to assessing local solutions with a standardised evaluation tool, and ending with jointly selecting promising strategies for implementation with the help of a decision support tool. The methodology is currently being applied in 16 study sites. Preliminary analysis from the application of the first part of the methodology shows that the initial stakeholder workshop results in a good basis for stakeholder cooperation, and in promising land conservation practices for further assessment. Study site research teams appreciated the valuable results, as burning issues and promising options emerged from joint reflection. The methodology is suitable to initiate mutual learning among different stakeholder groups and to integrate local and scientific knowledge.

Drivers of collaboration to mitigate climate change: An illustration of Swiss climate policy over 15 years

Climate change mitigation policy is driven by scientific knowledge and involves actors from the international, national and local decision-making levels. This multi-level and cross-sectoral context requires collaborative management when designing mitigation solutions over time and space. But collaboration in general policymaking settings, and particularly in the complex domain of climate mitigation, is not an easy task. This paper addresses the question of what drives collaboration among collective actors involved in climate mitigation policy. We wish to investigate whether common beliefs or power structures influence collaboration among actors. We adopt a longitudinal approach to grasp differences between the early and more advanced stages of mitigation policy design. We use survey data to investigate actors’ collaboration, beliefs and power, and apply a Stochastic Actor-oriented Model for network dynamics to three subsequent networks in Swiss climate policy between 1995 and 2012. Results show that common beliefs among actors, as well as formal power structures, have a higher impact on collaboration relations than perceived power structures. Furthermore, those effects hold true for decision-making about initial mitigation strategies, but less so for the implementation of those measures.

A methodology for appraising and selecting strategies to mitigate desertification based on stakeholder participation and global best practices

The main aim of the methodology presented in this paper is to provide a framework for a participatory process for the appraisal and selection of options to mitigate desertification and land degradation. This methodology is being developed within the EU project DESIRE (www.desire-project.eu/) in collaboration with WOCAT (www.wocat.org). It is used to select promising conservation strategies for test-implementation in each of the 16 degradation and desertification hotspot sites in the Mediterranean and around the world. The methodology consists of three main parts: In a first step, prevention and mitigation strategies already applied at the respective DESIRE study site are identified and listed during a workshop with representatives of different stakeholders groups (land users, policy makers, researchers). The participatory and process-oriented approach initiates a mutual learning process among the different stakeholders by sharing knowledge and jointly reflecting on current problems and solutions related to land degradation and desertification. In the second step these identified, locally applied solutions (technologies and approaches) are assessed with the help of the WOCAT methodology. Comprehensive questionnaires and a database system have been developed to document and evaluate all relevant aspects of technical measures as well as implementation approaches by teams of researchers and specialists, together with land users. This research process ensures systematic assessing and piecing together of local information, together with specific details about the environmental and socio-economic setting. The third part consists of another stakeholder workshop where promising strategies for sustainable land management in the given context are selected, based on the best practices database of WOCAT, including the evaluated locally applied strategies at the DESIRE sites. These promising strategies will be assessed with the help of a selection and decision support tool and adapted for test-implementation at the study site.

Extensive management of field margins enhances their potential to mitigate soil erosion

Soil erosion is a widespread problem in agricultural landscapes, particularly in regions with strong rainfall events. Vegetated field margins can mitigate negative impacts of soil erosion by trapping eroded material. In this data set, we present data of sediment trapped by 12 field margins during the monsoon season of 2013 in an agricultural landscape in the Haean-myun catchment in South Korea. Prior to the beginning of monsoon season, we equipped a total of 12 sites representing three replicates for each of four different types of field margins ("managed flat", "managed steep", "natural flat" and "natural steep") with Astroturf mats with a size of 34 cm x 25 cm (850 cm**2). The mats (n = 15 / site) were installed at three levels: upslope, immediately before the field margin to quantify the sediments that reach it, in the middle of the field margin to quantify the locally trapped sediments, and after the field margin at the downslope edge to quantify the sediments that leave the field margin to the next field or to the stream. Sediment was collected after each rain event until the end of the monsoon season.